Aegla singularis (ANOMURA, CRUSTACEA) USING DCCR EXPERIMENTAL PLANNING.Glutathione Reductase (GR) plays a key role in the maintenance of GSH homeostasis, variations in its activity may indicate damage from environmental contaminants.Experimental planning is a strategy to reduces time and cost in enzymatic assays.In this work, DCCR experimental planning was used to standardize and to validate the measure of GR in Aegla singularis bioindicator.Samples of A. singularis were collected in three watersheds with different percentages of naturalness and land uses.At all, were selected 7 streams, in which collections were performed at one upstream (most preserved) and one downstream (less preserved) point.Effects of temperature, reading time, substrate (GSSG) and protein concentration in GR reaction medium were evaluated, being that the two latter variables were optimized by DCCR.GR was not affected by temperature (15 to 30 °C) or reading time (6 and 10 minutes).Increased concentrations of proteins from biological extract had negative correlation with GR, whereas higher concentrations of GSSG resulted in higher GR activity.Environmental validation showed that GR in Aegla was influenced primarily by the watershed of origin.DCCR planning was efficient to optimizing the use of GR as a biomarker of environmental quality.

Glutathione Reductase (GR) plays a key role in the maintenance of GSH homeostasis, variations in its activity may indicate damage from environmental contaminants. Experimental planning is a strategy to reduces time and cost in enzymatic assays. In this work, DCCR experimental planning was used to standardize and to validate the measure of GR in Aegla singularis bioindicator. Samples of A. singularis were collected in three watersheds with different percentages of naturalness and land uses. At all, were selected 7 streams, in which collections were performed at one upstream (most preserved) and one downstream (less preserved) point. Effects of temperature, reading time, substrate (GSSG) and protein concentration in GR reaction medium were evaluated, being that the two latter variables were optimized by DCCR. GR was not affected by temperature (15 to 30 degrees C) or reading time (6 and 10 minutes). Increased concentrations of proteins from biological extract had negative correlation with GR, whereas higher concentrations of GSSG resulted in higher GR activity. Environmental validation showed that GR in Aegla was influenced primarily by the watershed of origin. DCCR planning was efficient to optimizing the use of GR as a biomarker of environmental quality.

With the growth of the product-service system (PSS) in recent years, how to better manage the service data to improve the informed decision-making capability has become an on-going aim among the Through-life Engineering Services (TES) firms. This scenario has led managers, more and more, to turn their attention to the quality of data and information created, gathered and used within the company. Encouraged by this background, a service data quality framework has been developed aiming to provide companies with a set of methods and tools to prioritise relevant service data and assess its quality levels. The process involves four main steps that go through: (1) Mapping out important data for Through-life Support available within the company and its internal and external flows; (2) Application of a multiple criteria decision-making technique to prioritise the relevant data set considering its costs for being collected and maintained, business impact, frequency of use and ease of obtainability; (3) Quality assessment of the prioritised dataset, based on a capability maturity model; (4) Defining strategies to address data quality issues. Validation on an industrial case study demonstrates potential benefits of the process and further work opportunities.